Big Data In Healthcare: Data Collection, Storage, And Business Continuity Essay.

Look at the big picture: besides describing the target audience, administrators should also focus on the big picture. They should consider staffing capacity and service lines to meet the existing needs. Healthcare sectors should consider what needs they are trying to meet and identify how to achieve that in an efficient way (King et al., 2011 p.596). They should be aware of their current end-user base and new end-user based that they could serve in future.

• Empathy: they should feel care from the providers
• Economy-: they should feel that they are acquiring a fair value
• Experience: it should result to a cure
• Efficiency: they should not wait for long
• Empowerment: they should be able to make decisions about their plans of treatment.

You are required to discuss the following topics in depth. Your discussion should display deep analysis of issues with no irrelevant info.

Task 1. Data Collection and Storage

• Data collection system (what kind of data should be collected and how)
• Storage system (what are the requirements to the storage and how to achieve them)

Task 2. Data in Action

Consumer-centric product design (what is it and how to do it)

• Recommendation system (what is it and how to do it)

Task 3. Business continuity

• How online business can survive in case of power outage or other disasters?

The Importance of Looking at the Big Picture

Big Data is the popular phrase today. It is mentioned everywhere, particularly in the healthcare sectors. Traditionally, the massive amount of information created by the healthcare industry was kept as hard copy. The data has the potential support an extensive range of medical and healthcare functions. Digitizing such information is referred to as Big Data (Kumari and Dr.K., 2018 p.72). Data entirety that is connected to the well-being and health care of a patient makes up big data. A McKinsey report in 2011 approximated that the industry of health care could probably earn an annual value of $300 billion by using big data.

The extensive big data diversity and the speed at which it is controlled is overwhelming. In consists of medical data from Computerized physician order entry (CPOE) and medical decision support systems (medical imaging, pharmacy, physicians written prescriptions and notes, laboratory, insurance, among other administrative data); machine sensor/generated data (for instance, from monitoring critical signs), less patient-specific data such as news feeds, emergency care data and medical journals articles; and social media posts such as blogs, web pages, Twitter feeds and status updates on Facebook and other channels.

Big data is essential in the healthcare sector. Over the past 10 years, EHR (electronic health records) have been extensively embraced in clinics and hospitals globally. Such data can be used to gain deeper knowledge about the disease pattern of a patient and important medical knowledge. It will assist in improving efficiency and patient care.

The healthcare system has various main health data pools that are managed by various parties/stakeholders:

Clinical data: it is managed by the provider such as care centers, hospitals, physicians, among others, and include any data kept within the EHR and HIS (hospital information systems, such as medical images, genetic data, medical records, lab results, among others (McGuckin and Govednik, 2015 p.348).

Cost, claims and administrative data: it is managed by payors and providers and includes any dataset applicable for issues of reimbursement such as cost estimates, use of care, claims and others.

Research data: it is managed by the research academia/labs, pharmaceutical organizations and government, and includes clinical studies, disease data, clinical trials and population.

Patient monitoring data: it is managed by the monitoring device producers or patients and includes any data connected to patient preferences and behaviors (Hopf et al., 2014 p.e3).

Health information on the web: websites for instance PatientsLikeMe are becoming famous to a greater extent. By sharing information voluntarily about remarkable experiences and rare diseases with their communities, common diseases and users are creating large health datasets with important content.

• Study staff
• The investigator
• Directly by patients (referred to as PROs (Patient-Reported Outcomes))

Understanding Big Data in Healthcare

It can happen through the traditional way, for instance on paper such as patient diaries, CRFs (Case Report Forms) or questionnaires. It can also occur in electronic ways, for example in eCRFs (electronic CRFS), or by utilizing hand-held tools such as tablets or mobile phones to gather information directly from patients (electronic PROs (ePROs)) (Park, 2015 p.64). Another technique of gathering information is referred to as DDC (Direct Data Capture). In DDC, information is directly created by electronic instruments and keyed into the database.

Paper CRFs (Case Report Forms)

Paper Case Report Forms are structured for handwritten information. They are inexpensive to generate and permit the generation of faxing and direct copies. modern technology such as OCR (optical character recognition) permits computers to look at and understand the data written by site worker and key in them automatically into a database.

eCRFs (Electronic Case Report Forms)

eCRFs are becoming famous to a greater extent. Nevertheless, they are complex to generate and need to follow strict rules. The computer software or programs must be verified and every adjustment that is made to the information keyed in must be trackable. They must make sure that only approved individuals have access to the data and the program. Backups of data must be done automatically and regularly (Sathiyavathi, 2015 p.123). Utilizing eCRFs in an analysis needs all sites investigator to have reliable and adequate access to the internet and computers. Besides, site staff utilizing the eCRF should undergo intensive training.

DDC (Direct Data Capture)

• ECG (Electrocardiogram) data
• Electronic patient diaries/questionnaires
• Laboratory data
• Central image reading (MRI (Magnetic Resonance Imaging) results)

PROs (Patient Reported Outcomes) and ePROs (Electronic capture PROs)

The term PRO (Patient Reported Outcome) is applied for all information that is directly offered by patients. It encompasses all kinds of diaries and questionnaires. It can be written using electronic systems or on paper. Technical devices that can be utilized to collect this information in a participant-friendly and efficient manner are quickly emerging. If a hand-held electronic system such as SMS (text messaging) or tablet is utilized, the phrase ePRO is utilized (Teale, Young and Sleigh, 2013 p.11). Usually, this electronic information is either in form of QoL (Quality of Life) questionnaires carried out during sites visits or daily diary at the home of the patient.

Healthcare institutions are developing their IT foundation to be more scalable and flexible to meet the increasing need of data. With the growing number of networked clinical devices consistently receiving data and value-based inducement for data analytics, companies face difficulties with storing medical information in a manner that id both easy for approved persons to access and HIPAA-compliant.

Types of Health Data Pools

Traditionally, healthcare institutions have refrained from cloud data storage in the interest of on-premise alternatives because of the authority administrators of IT have over physical data storage. Nevertheless, the likelihood of entities to put into effect cloud storage into their IT framework is high because of the enhanced HIPAA-compliance and minimized costs of maintenance.

The options of cloud data storage provide a scalable and flexible environment at a cheaper price than on-premise implementations, which is attractive to covered bodies. Companies investigating data analytics are anticipating their requirements about storage to steadily grow as mobile devices and IoT (internet of things) collect information that needs to be kept (ZHOU and ZHOU, 2013 p.310).
one of the main challenges of data storage healthcare institution encounter is how to put together legacy systems while connecting new systems into the framework. Many bodies find it challenging to mass move data from a single storage system to another, that is why interoperability between various vendors of cloud is needed for a smooth change. Some healthcare institution enjoy benefit from different type of data storage, as such, selecting a storage deployment may be challenging for any company.

However, the cost efficiencies and benefits acquired from shifting to the cloud are many, including:

• More smooth cooperation among geographically distributed healthcare patients and entities
• The ability to backup and secure data cheaply
• The ability to share data securely and easily
• Flexibility and scalability.

For providers of health care to safely leverage Cloud services or SaaS and take joint responsibility for data protection and management, the following requirements should be met:

Security and privacy: develop powerful Service Level Agreements with the provider of cloud service regarding privacy and security. Healthcare institutions must have knowledge of how and where electronic secured health data is stored or moved by the provider.

Compliance and regulation: Implementation of compliance measures and security controls should be needed by cloud provider, but fundamentally, compliance responsibility is always found within the healthcare body. Cloud providers must offer solutions that complies with HIPAA. Companies must ensure that the information entrusted to a cloud provider have breach notification and regulatory/legal protection requirements such as PHI (protected health information) managed by HITECH and HIPAA, and PII (personal identifiable information) managed by state privacy laws.

Data protection and backup: healthcare industries should put into effect a cloud backup strategy to make sure their data is not vulnerable to events of data loss such ass ransomware attacks, accidental deletions or human error, and is always accessible. Backup solutions for cloud must agree with RTO (recovery time objectives) and must offer unlimited access to backup data. Data protection and backup must follow the regulations of HIPAA. Backups should be carried out on demand or daily.

Data Collection Techniques: Paper CRFs, eCRFs, DDC, PROs and ePROs

Data restore requirements: data of individuals should be maintained in the same format as it was before the backup. It should not be encrypted. Functionality restoration should be unprocessed and offer a limited time snapshot of information. restoration of data should occur into a consumable format and easily and backups should be easy to monitor.

Object storage is a cost-effective and simple solution that has evolved and assist in curbing challenges faced by healthcare industries while following the strict regulatory requirements regarding security protocols, how fast data can be accessed, data privacy and the period the data must be retained.

Traditional systems of storage usually arrange data in blocks or files, nevertheless, with object storage, storage units are arranged in objects. After storing the object, an ID is created for it so it can be found in a pool of storage (Ben Amor, Lahyani and Jmaiel, 2018 p.57). Applications can rapidly restore the appropriate information by looking for the object metadata or through object’s ID. Besides, objects are unrestricted by a stratified file structure, as such, number of IDs of the object can be scaled and increased virtually without limit. Every time object changes, it is kept as a new object to avoid misrepresentation. Besides, storage of the object uses code deletion to assist in maintaining data integrity and retrieve corrupted or lost data by utilizing redundant chunks.

Objects are safeguarded because several copies of information are kept over a distributed system. If a node fails, the information can still be accessible, which addresses common problems such as bit-rot, power outages, drive failures and server failures. Most healthcare institutions are required by the HIPAA Privacy Rule to put into effect proper technical, administrative and physical defense to safeguard the privacy of PHI (protected health information) for whatever period the information is retained.

Object storage assist on side of storage by offering resilient replication, built-in security and erasure coding. Although the HIPAA Privacy Rule does not encompass requirements of data retention for clinical records, state laws do. Clinical trial data, patients records and other types of information related to health should be kept for years.

Furthermore, information must be searchable, secure and accessible, which is offered by object storage. Through object storage, information can be obtained from anywhere and at any time through connection to the internet. Besides, it is easy to locate and search information by querying the object metadata or using the ID of the object.

The Benefits of Cloud Data Storage in Healthcare

In addition, healthcare institutions can search for a bundle of documents that meet particular criteria. For example, an X-ray kept as a document would have inadequate metadata linked with it, apart from the date and a name it was generated. If it was kept as an object, nevertheless, the X-ray could contain adequate metadata data, such as the injury type, the age and gender of the patient, the area of the body X-rayed and the injury case (CHEN, XIAO and LIU, 2013 p.338). It ascertains simple and useful for users to quickly restore particular data.

Healthcare data usually contains large size files or large data sets, such as X-rays, videos and electronic health records. Besides, object storage can accommodate it all because it can scale limitlessly and it has native large data sets support. Architectures of object-based storage can be controlled easily by increasing additional nodes.

In addition, object storage is economical, a key benefit for healthcare companies who are aware of the budget. As the healthcare industry consistently keeps zettabytes of information, many companies will constantly embrace object storage as a cos-effective, simple and scalable solution to meet their demands.

Data is essential to healthcare providers as the latest development or medical journals in medical and pharmaceutical devices. The sector has traditionally concentrated on reactive cures to issues, like controlling high cholesterol using satins. Nevertheless, people are becoming more knowledgeable that prevention and prediction of illness is cheaper and more effective than reactive solutions.  An example is the emerging idea of PHM (population health management). In the first place, providers work to ensure people are healthy than rely on costly treatments such as emergency room visits and acute care. To ensure that PHM is working, providers rely on data analysis and collection. Beside EHR, companies look at an extensive data sources to establish comprehensive patient records. To make other approaches and PHM to prevention and anticipation work, providers require a more advanced procedure to utilizing data. Analysis, collection and action must be done in consideration of real-time.

For healthcare leaders who desire to expand their knowledge in this sector, it can be helpful to think about things from the perspective of a customer so as to structure an end-user-centered experience that will act reasonably to its potential. Nowadays, clinicians and healthcare institutions do not take all the accountability for making decisions on how patients will be treated. Due to advances effectuated by healthcare transformation, including the growing insistence on value-driven care and client satisfaction, many individuals are actively involved in their healthcare.

Requirements for Secure Cloud Data Storage

To appreciate the true benefit of employing customer-centricity in the health sector, leaders must first acknowledge the existing realities found in the healthcare system. When the costs of healthcare are high, the industry concentrates on centralized regulations and cost efficiency that are structured to govern in those costs. It can make the top employees to be demotivated and report bureaucracy, and also, it can result to poorer outcomes. A customer-centric strategy can work to transform the scenario by changing the concentration to the end-users themselves, engaging them better in their care procedures (Dafferianto Trinugroho, 2014 p.141). For example, a customer-centric strategy enables patients to collaborate with physicians to understand their treatment options and health risks and to engage in an active role of making their choices. If an end-user participates in researching his or her health issue, he will probably also take part in his preventive care. Taking such actions of preventions can assist in boosting quality of life and self-esteem, saving money and achieving better devotion to practitioner recommendations.

Adjust efforts to meet various patient segments: when structuring a customer-centric strategy for an institution, it is essential to acknowledge that not all patients are equal and thus, how the challenge is approached may change depending on the target. One need to understand the existing end-user base and profile potential end-users that are likely to be served in future. By determining the individuals to be reached, one can adjust the outreach and marketing efforts to develop efficient working alliances.

Look at the big picture: besides describing the target audience, administrators should also focus on the big picture. They should consider staffing capacity and service lines to meet the existing needs. Healthcare sectors should consider what needs they are trying to meet and identify how to achieve that in an efficient way (King et al., 2011 p.596). They should be aware of their current end-user base and new end-user based that they could serve in future.

The following are some of the elements of consumer-centric care:

• Empathy: they should feel care from the providers
• Economy-: they should feel that they are acquiring a fair value
• Experience: it should result to a cure
• Efficiency: they should not wait for long
• Empowerment: they should be able to make decisions about their plans of treatment.

A recommendation system is a system used to filter information and handles the problem that has been brought about by increasing volumes of information available. In health industry, such systems are used to sieve important information from the vast amount of data available in the health center data centers according to the user requirements (Huang and Fang, 2013, p. 1227). Recommender systems has numerous advantages both to the hospital staff and patients. Additionally, recommendation systems have enhanced the process and quality of the decisions made. The main objective of the recommendation systems in health care is to supply users (Physicians and patients) with relevant medical information in order to make the right decisions.

Object Storage: A Cost-Effective Solution for Healthcare Institutions

To develop a reliable and secured recommendation system, it is necessary that all the requirements are specified. Functional, privacy, and reliability requirements should be laid out well because they guarantee system integrity and information privacy.

Functional requirements ensure that the recommendation system does what is expected to do. For instance, maintain a record of health conditions and physician/doctor list for which recommendations can be given (Isinkaye, Folajimi and Ojokoh, 2015, p. 269). A case example is, if a patient contributes information about a particular condition he/she is suffering from and the physician who treated him/her, the system should automatically reflect the satisfaction of the patient being treated that particular condition by the specific physician and is chosen form publicly known and pre-define range.

Privacy requirements is another critical aspect that recommender system should have. When users contribute information, many at time it is treated as public information. However, in the medical sector such information given by patients is strictly confidential and should not be accessed by outside/unauthorized parties. Medical applications should not allow public ratings. Therefore, recommendation systems should not require patients to divulge their information.

Reliability Requirements ensure that the recommendation system should detect any incorrect input and should at all times give desired results given the normal operational conditions. The system should also protect physicians from dishonest competitors and unreasonable users, that is, a physician’s reputation should not be sabotaged by a small group of users (Wiesner and Pfeifer, 2014, p. 2593).

Disasters can greatly affect the daily operations of a business. For the health industry the effects can be adverse because life may be lost. Power outage for instance may lead to malfunction of critical systems in hospitals such as life support machines, and in cases where there are no backup generators, this means that lives that depend on these machines will be lost (Costello, 2012, p.64). Because of this, it has become crucial to have a robust business continuity plan that contains all the critical aspects of a health system. When creating a business continuity plan (BCP), it is essential that the team developing it is multi-disciplinary because of the vast amount of information required from the several departments.

Additionally, the team should be able to gather information and work the several departments within a hospital setup. BCP team can consider several scenarios as they develop the BC plan. The most common scenarios that could halt the operations of a health center include power outage, natural disasters (earthquakes, floods), inaccessibility of the facility, unavailability of vendors or critical staff, failures of computer systems, equipment not operational, data corruption, or utilities are down (Lee and Guster, 2010, p. 74). Therefore, The BC team will have to closely work with every department to establish the processes that are needed to be functional and the give a priority to those that are critical. Systems will then be established to ensure that the critical processes can continue operating during and after a disaster.

Core Elements of Business Continuity Plan

A BC Plan should contain some core elements as much as it can be modified to meet the health center requirements. This section will discuss the core elements that are required in most plans.

The Business Continuity program at the health center must be supported by the senior leadership. The Executive Summary commits this group to take responsibility for creating, maintain, testing and implementing this plan. Executive summary contains several essential information about the BCP. For instance, what the business plan is all about, the content of the BCP, Importance of the BCP to the health center, what the BCP covers, commitment of the health center to ensure continuity of critical services during and after a disaster, and the importance of regularly conducting drills and trainings.

Business Continuity Planning Team

BCP team is a group of staff members from the various departments across the health center that is responsible for developing the BCP to ensure that every sector of the health center is represented. The team will evaluate the completed BCP with all the departments and the senior management to make sure that it is relevant, accurate, and has captured all the necessary details (Ghandour, 2014). The team is also responsible for conducting training, drills, review, and update of the BCP.

Hazard Vulnerability Analysis

Regular update of the hazard vulnerability analysis should be done. Hazard vulnerability analysis (HVA) is one of the critical tools required for hazard mitigation planning. HVA aids in identifying vulnerabilities that hazards may cause to the health center and the possible direct and indirect impacts (Lee and Kim, 2013, p. 39).  HVA results will aid the health center in emergency planning and in identifying the following: Hazards that can affect the hospital, expected impacts, and the mitigation strategies. The information gathered gives a snapshot of the possible risks that every hazard has on the health center. Hazards with high risk number will have more efforts on determining the best mitigation plans and strategies.

Determine the processes that every department requires to ensure that critical functions continue running in case of disruptive incidences and the period that every process can be halted before it is rendered unacceptable. Business impact analysis (BIA) gives detailed information about all the health center processes (Ghandour and Benwell, 2012, p. 263). The processes of every department are then evaluated in-depth so as the team gets the overall picture of the non-critical and critical processes. If the processes require particular procedure it is essential to develop steps on how to carry out such processes. Furthermore, it is necessary to understand any legal and regulatory requirements that that directly regulates specific operations within the health center that have to be kept in case of a disruptive incident. Additionally, it is important to identify the crucial requirements that incase the health center needs to be moved to an alternative location it will still operate (Zhang and McMurray, 2012). When carrying out process review it is necessary to consider two aspects; time and data:

Time analysis is carried out to identify the amount of time acceptable during downtime before its operation must be brought back. Recovery time objective is the minimum service level and maximum time accepted before a process is restored after interruption (Watanabe, 2012, p. 343). Data analysis on the other hand describes the type and amount of data that must be present so as to allow operations of the health center to go on. Recover point objective describes the maximum acceptable time for data unavailability due to disruption before recovery.

After completing the BIA on every departments and within the hospital, the information collated will aid the institution in determining the areas that need to be protected at all times to minimize or prevent downtimes (Heng, 2015, p.11). The BCP team has the responsibility to develop mitigation procedures, strategies, backups and protection for the health institution, for example: Reinforced structures both external and external at the physical site, redundant third-party support should be created, fire detection and suppression systems should be functional and current, back-up procedures and systems should be developed for software and computers.

Some of the Mitigation procedure and strategies that will support continuity of health center operations include:

• Offsite backup systems for essential software, data, and critical facilities.
• Alternatives in case of disruptions such as backup generators, alternative communication, records and data, facilities, and staff.
• Steps to integrate necessary inventory of essential equipment

Mitigation policy should also be defined in order to give direction to the accomplishment of these activities (Boisvert, 2011, p. 15). It is important to ensure that the policy describes why it is important to have mitigation strategies in place.

The health center should be able to respond efficiently and quickly in cases of disruptions to ensure that hospital operations are maintained. As such, procedures should be developed before such disruptions occur to ensure that the critical operations are not affected and strategies have been laid out to ensure operation and systems recovery (Rinehardt, 2010, p. 1606). Recovery strategies should be developed for the different categories of disruptions (equipment, technology, facility, and staff) that covers nearly every incident that the health center may encounter.

Conclusion

Health data analytics and Big data technologies offer the ways to solve the quality and efficiency problems in the health domain. For example, by analyzing and aggregating health information from different sources, such as financial, clinical and administrative data, the treatment results regarding the use of resources can be controlled. Besides, the analysis assists in improving the effectiveness of care. Furthermore, the determination of patients with high risks using predictive methods result to proactive patient care, thus delivering high quality care.

A detailed analysis of domain requirements and needs showed that the greatest effect of big data applications in the healthcare sector is attainable both through acquisition of data from one source and from different data sources such as various aspects can be joined together to acquire new insights. As such, the integration and availability of all connected health data sources, such as cost, claims and administrative data, sentiment and patient behavior data, clinical data, R&D and pharmaceutical data, and the health information on the web, is of great importance.

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